Using Bubble Plots to Aid in Extension Program Planning

Abstract
Mailing lists are an excellent method for
sending information to clientele about research, field days, or
upcoming educational events. The objective of the project described
here was to determine if bubble plot mapping could be used to analyze
a mailing list to maximize the impact of future educational programs.
Latitude, longitude, city, and the number of clientele in each city
were used to create a bubble plot with overlays of Arkansas
boundaries. The bubble plot overlay provides an easy way to interpret
the mailing list, which aids in selecting locations to plan future
events in areas where clientele impact will be greatest.

Introduction

One vital component to every good Extension
program is to have an up-to-date mailing list of clientele (Torell,
Bruce, & Kvasnicka, 1999). Mailing lists are a great way to send
information to clientele about research, field days, or upcoming
educational events. When new programs are developed/enhanced or new
specialists are hired, there may be a need to develop a mailing list.
Existing Extension lists (producers, agents, and specialists), the
yellow pages, directories of stakeholder groups such as
associations/organizations, registrations, city and state records,
and colleagues are all sources important in the development of a
mailing list (Israel, 1993). If available, the list should include
more than the contact information, such as helpful information about
gender, business type, crop, specific interests, etc., which will
allow the list to be sorted to help identify useful subgroups in the
mailing list.

In addition to developing the list, it is
important to properly interpret the list. It would be particularly
helpful to know where the majority of the clientele are located so
that programs could be created and offered in those locations. The
objective of the project described here was to determine if
statistical software and bubble plot graphing could be used to
analyze a mailing list to better plan and maximize the impact of
future turfgrass educational programs in Arkansas.

Method

Step 1. List. Create a mailing list
database for your clientele. As an option in this database additional
information such as gender, business type, crop, specific interests,
etc., can be included.

Step 3. Distribution. Using JMP® or
another statistical software package, determine the distribution
(count or number) of your clientele for each city. NOTE: This is an
opportunity to combine mistyped or multiple typings of a city/town
(e.g., Ft. Smith, Ft Smith, Fort Smith) to get the correct
distribution.

Step 4. Location. Merge latitude and
longitude data from an external database for each city with the data
gathered in the previous step. NOTE: This data is usually available
from GIS/GPS specialists or from helpful Web sites such as
<http://geonames.usgs.gov/pls/gnispublic/>.

Step 5. Bubble plot. Bubble plots can
be created in JMP with up to six dimensions; X, Y, size, ID, color,
and time. Create a bubble plot using JMP® with latitude was the Y
component, longitude the X component, city/town as the
identification, number (count) of clientele per city/town as the size
and color component. The time component was omitted in the experiment
reported here. Bubble size can be adjusted with a sliding size
selector to allow for better interpretation.

Step 6. Mapping. Create a city, state,
region, or country map. In this example, a JMP® script was already
available for Arkansas. A digital image of the state, region, or
country will also suffice if none is available.

Step 7. Overlay. Overlay the images
created from steps 5 and 6. This may require some resizing in order
for the images to properly align. This can be done in JMP® by
copying the image from step 6 and pasting onto the bubble plot.
Additionally, JMP scripts can be modified by expert programmers to
include a map as part of step 5. Other image editing programs such as
Adobe® Photoshop® can also be used to resize and overlay images
created from steps 5 and 6.

Step 8. Interpret. Visually assess the
total clientele distribution and by subgroups in order to determine
locations with critical needs. Cities with overlapping bubbles
indicate a critical need.

Findings and Discussion

The distribution of the mailing list (n=1350)
indicated that there were many cities with multiple clientele (Table
1). Further analysis of this distribution with bubble plot mapping
overlayed with Arkansas state and county boundaries provided a
graphical interpretation of where these cities were located and the
size of the clientele base (Figure 1). Bubble color and size
indicated the number of clientele on the mailing list from a
particular city/town. Large or overlapping bubbles indicated areas
where clientele population is high and where program impact could
also be high because bubble size is based on clientele size.

The bubble plot overlay (Figure 1) identified
three critical areas where clientele impact would be greatest:
Northeast, Northwest, and Central Arkansas. When the entire mailing
list analysis (Figure 1) was compared with a population distribution
map of Arkansas (Figure 2), it was apparent that the majority of
turfgrass clientele were located in areas with high population
densities. This is not completely unexpected because it is known that
turfgrasses are most commonly used in urban landscapes (Milesi et
al., 2005) and that turfgrass professionals work in these areas.

Table 1.
Distribution of Clientele in
Cities with ≥10 Clientele/City

City

Count

Little Rock

101

Fayetteville

47

Jonesboro

44

North Little Rock

32

Fort Smith

30

Conway

27

Springdale

26

Hot Springs

22

Searcy

22

Sherwood

16

Bella Vista

15

Cabot

15

Maumelle

15

Rogers

15

Perryville

14

Benton

13

Paragould

13

Bentonville

12

Hot Springs Village

12

Mountain Home

12

Pine Bluff

12

Russellville

11

Arkadelphia

10

Texarkana

10

Figure 1.
Bubble Plot Overlay of Arkansas
Turfgrass Clientele

Figure 2.
Population Map for Arkansas

Although the turfgrass industry as a whole is
associated with urban areas, not all subsets of the turfgrass
industry are located in urban areas. Distribution of current or
retired turfgrass (sod) producers in Arkansas (n=67, subset of
dataset) indicated that the majority of turfgrass producers are in
central Arkansas or are located in rural areas in close proximity to
central Arkansas or another population center (Figure 3). For
example, the largest group of sod producers in Arkansas are located
northwest of Little Rock (Pulaski county, central Arkansas) in rural
areas in Perry county.

This article is not the first attempt to
graphically analyze a mailing list. Bazik and Feltes (1999) proposed
using zip code in combination with GIS software to visualize the
physical distribution or demographic characteristics of certain
populations. Regardless of the exact method used, it is important to
attempt to better analyze and understand the location of clientele so
that programs can be developed in critical areas.

Conclusion

The bubble plot map overlay allowed for
rapid, easy interpretation of the geographic areas with the greatest
number of clientele. Bubble plots provide a graphical way to
interpret the data from a mailing list, which aids in selecting
locations for site visits or sites for educational events
specifically in areas where high clientele populations exist and
where impact will be greatest.

Acknowledgements

I thank Vinod Shivrain, research assistant in
the Crop, Soil, and Environmental Sciences department at the
University of Arkansas, for providing a JMP script that mapped the
Arkansas county and state boundaries. Additionally, I thank Malcolm
Williamson from the Center for Advanced Spatial Technologies (CAST)
at the University of Arkansas for providing a detailed list of
latitude and longitude data for Arkansas cities and towns.